A look across application areas and diverse products reveals that a re-occurring keyword is “intelligence.” In areas such as web intelligence for business applications, coordination of robotic teams for NASA’s exploration vision, DOD’s net-centric approach, and network security, all applications are expected to incorporate “intelligence.” The intelligence may be required for an application to succeed, or it may be an enhancement over a “dumber” version; the keyword “intelligence” now serves as a system or product discriminator. Intelligence may also emerge from simpler interactions within the distributed system. The definition and focus of intelligence also seems to be varied. One of the newest application areas involves humans in the loop via distributed social intelligence. An element of the intelligence in this area involves tapping into collective human opinion.

The development of intelligence is the overarching focus of the artificial intelligence field. To this end, various paradigms have been developed which offer approaches to support the development of intelligence within an application. Among these paradigms are the bioinspired or biomimetic, social or organizational-based, algorithm-based, cognitive, logic-based, knowledge-based, hybrid, and so on. Additionally, methodologies which are utilized to build intelligent systems may include intelligence technology themselves. For example, software verification and validation efforts may utilize theorem provers based on computational logic. This symposium provided a venue to consider, as a set, the (1) paradigms and associated algorithms that support intelligence and (2) distributed systems that incorporate intelligence, with enabling methodologies for expression of intelligence on the system level.